Characterization of Bioactive Recombinant Human Lysozyme Expressed in Milk of Cloned Transgenic Cattle

BACKGROUND: There is great potential for using transgenic technology to improve the quality of cow milk and to produce biopharmaceuticals within the mammary gland. Lysozyme, a bactericidal protein that protects human infants from microbial infections, is highly expressed in human milk but is found in only trace amounts in cow milk. METHODOLOGY/PRINCIPAL FINDINGS: We have produced 17 healthy cloned cattle expressing recombinant human lysozyme using somatic cell nuclear transfer. In this study, we just focus on four transgenic cattle which were natural lactation. The expression level of the recombinant lysozyme was up to 25.96 mg/L, as measured by radioimmunoassay. Purified recombinant human lysozyme showed the same physicochemical properties, such as molecular mass and bacterial lysis, as its natural counterpart. Moreover, both recombinant and natural lysozyme had similar conditions for reactivity as well as for pH and temperature stability during in vitro simulations. The gross composition of transgenic and non-transgenic milk, including levels of lactose, total protein, total fat, and total solids were not found significant differences. CONCLUSIONS/SIGNIFICANCE: Thus, our study not only describes transgenic cattle whose milk offers the similar nutritional benefits as human milk but also reports techniques that could be further refined for production of active human lysozyme on a large scale

Synchronization of Nonlinear Complex Spatiotemporal Networks Based on PIDEs with Multiple Time Delays: A P-sD Method

This paper studies the synchronization control of nonlinear multiple time-delayed complex spatiotemporal networks (MTDCSNs) based on partial integro-differential equations. Firstly, dealing with an MTDCSN with time-invariant delays, P-sD control is employed and the synchronization criteria are obtained in terms of LMIs. Secondly, this control method is further used in an MTDCSN with time-varying delays. An example illustrates the effectiveness of the proposed methods

Integrated approach to diagnose structural behavior of dam

10.1080/19648189.2023.2216742European Journal of Environmental and Civil Engineering282457-47

Re-examining the suitability of high magnesium nickel slag as precursors for alkali-activated materials

High-magnesium nickel slag (HMNS) has shown the potential as precursor in the production of alkali-activated materials (AAMs). This study re-examines the suitability of HMNS by comparatively investigating the reactivity of four different sourced HMNSs and analyzing impacts of the magnesium sources in HMNS on the reaction products of AAMs. Results show that the cooling way plays a determinant role of their mineral compositions. The air-cooled HMNSs contain only ∼30 wt% glassy phases, while the water-quenched one is dominantly amorphous. The reactivity of HMNS determined by the dissolution tests correlates well with the calculated depolymerization degree of glasses. HMNS indeed exhibits lower reactivity than the precursors commonly used for AAMs production, such as fly ash and blast furnace slag. In the HMNS samples in the sodium hydroxide solution, M-S-H, C-S-H and hydrotalcite are the main reaction products. The OH− ions in the aqueous system react with Mg2+ to form the brucite, indicating that there is still a volume expansion risk if sodium hydroxide is used as activator. In comparison, only M-S-H and C-S-H gels are coexistent in the samples leached in the sodium silicate solution, because of the kinetic hindrance of soluble silicates for the formation of hydrotalcite and brucite

Canonical Correlation between the Leaf Quality Indicators of "Moderate Aroma" Flue-cured Tobacco

In order to find out the correlation between tobacco quality evaluation indicators in China's traditional "moderate aroma" tobacco-producing areas and simplify the tobacco quality evaluation indicators, we evaluate the appearance quality and smoking quality of 143 flue-cured tobacco leaf samples in China's "moderate aroma" tobacco-producing areas, test the physical traits and chemical component, and analyze the canonical correlation between four quality evaluation indicators. The results show that there is significant or extremely significant canonical correlation between four evaluation indicators (tobacco smoking quality, chemical component, appearance quality and physical trait quality); the cumulative variance contribution rate of evaluation indicators is in the order of chemical component (69.17%)>appearance quality (68.76%)>physical traits (64.13%); appearance quality is most closely related to physical traits (93.84%). The individual indicators for tobacco quality evaluation make different contribution to the correlation between quality evaluation indicators. The chemical component evaluation indicators mainly include total sugar and ratio of total sugar to betaine; sensory taste indicators mainly include aroma volume, smoke concentration, irritation and softness degree; physical trait evaluation indicators mainly include leaf weight, leaf length and leaf density; appearance quality indicators mainly include leaf organizational structure, color, maturity and identity. Studies have shown that in the large-scale eco-region, using canonical correlation analysis to simplify tobacco quality evaluation indicators is feasible

Analysis of Regulation Characteristics in Acceptable Thermal Comfort Zone under Cooling Conditions

Residents mainly set the temperature at the range of 25°C to 27°C under cooling conditions. However, they may feel uncomfortable after staying a period in a steady-temperature environment. To make themselves more comfortable, residents will change their postures and even regulate the temperature. To analyze the regulation characteristics, this study combined thermal environment testing, questionnaire survey, video collection, and data mining methods to collect the thermal environment and comfort background, posture, and temperature regulation characteristics. The results showed that Mean Thermal Sensation Vote gradually deviated from neutrality and tended to be cooler even though the thermal environment and thermal comfort were both within the acceptable zone. 12 typical posture regulations were captured and divided into 3 categories: head (face) postures, trunk postures, and limb postures. Head (face) postures were the concentrated expression of adaptive postures (80%). Although the total posture frequency remained unchanged, the head (face) postures gradually increased, which reflected the increase in discomfort. The temperature regulations accounted for nearly 25%. Most people (90%) regulated the temperature at 1 °C with the frequencies of once or twice, and they preferred to set the temperature up than down. In the first 3 hours, there would be a regulation peak every 20 or 30 minutes, while the regulation decrease after 3 hours

Improving Plot-Level Model of Forest Biomass: A Combined Approach Using Machine Learning with Spatial Statistics

Estimating the aboveground biomass (AGB) at the plot level plays a major role in connecting accurate single-tree AGB measurements to relatively difficult regional AGB estimates. However, AGB estimates at the plot level suffer from many uncertainties. The goal of this study is to determine whether combining machine learning with spatial statistics reduces the uncertainty of plot-level AGB estimates. To illustrate this issue, this study evaluates and compares the performance of different models for estimating plot-level forest AGB. These models include three different machine learning models [support vector machine (SVM), random forest (RF), and a radial basis function artificial neural network (RBF-ANN)], one spatial statistic model (P-BSHADE), and three combinations thereof (SVM & P-BSHADE, RF & P-BSHADE, and RBF-ANN & P-BSHADE). The results show that the root mean square error, mean absolute error, and mean relative error of all combined models are substantially smaller than those of any individual model, with the RF & P-BSHADE combined method generating the smallest values. These results indicate that a combined approach using machine learning with spatial statistics, especially the RF & P-BSHADE model, improves the accuracy of plot-level AGB models. These research results contribute to the development of accurate large-forested-landscape AGB maps.Science, Irving K. Barber Faculty of (Okanagan)Non UBCEarth, Environmental and Geographic Sciences, Department of (Okanagan)ReviewedFacultyResearcherOthe

Determining the Mechanisms that Influence the Surface Temperature of Urban Forest Canopies by Combining Remote Sensing Methods, Ground Observations, and Spatial Statistical Models

The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of spatial patterns of urban cool islands. This quantitative research uses an integrated method that combines remote sensing, ground surveys, and spatial statistical models to elucidate the mechanisms that influence the STUFC and considers the interaction of multiple environmental factors. This case study uses Jinjiang, China as a representative of a city experiencing rapid urbanization. We build up a multisource database (forest inventory, digital elevation models, population, and remote sensing imagery) on a uniform coordinate system to support research into the interactions that influence the STUFC. Landsat-5/8 Thermal Mapper images and meteorological data were used to retrieve the temporal and spatial distributions of land surface temperature. Ground observations, which included the forest management planning inventory and population density data, provided the factors that determine the STUFC spatial distribution on an urban scale. The use of a spatial statistical model (GeogDetector model) reveals the interaction mechanisms of STUFC. Although different environmental factors exert different influences on STUFC, in two periods with different hot spots and cold spots, the patch area and dominant tree species proved to be the main factors contributing to STUFC. The interaction between multiple environmental factors increased the STUFC, both linearly and nonlinearly. Strong interactions tended to occur between elevation and dominant species and were prevalent in either hot or cold spots in different years. In conclusion, the combining of multidisciplinary methods (e.g., remote sensing images, ground observations, and spatial statistical models) helps reveal the mechanism of STUFC on an urban scale

Nature and significance of the late Mesozoic granitoids in the southern Great Xing’an range, eastern Central Asian Orogenic Belt

<p>Abundant late Mesozoic granitic rocks are widespread in the southern Great Xing’an Range (GXAR), which have attracted much attention due to its significance for the Mesozoic tectonic evolution in the eastern Central Asian Orogenic Belt. However, controversy has still surrounded the late Mesozoic geodynamic switching in the continental margin of east China, especially the spatial and temporal extent of the influence of the Mongol-Okhotsk and Palaeo-Pacific tectonic regimes. In order to better understand the Late Mesozoic evolutionary history of the southern GXAR, a number of geochemical, geochronological, and isotopic data of the granitoids in this region are collected. Magmatism in the southern GXAR can be divided into six phases: Late Carboniferous (325–303 Ma), Early-Middle Permian (287–260 Ma), Triassic (252–220 Ma), Early Jurassic (182–176 Ma), Late Jurassic (154–146 Ma), and Early Cretaceous (145–111 Ma). Mesozoic magmatic activities in the southern GXAR peaked during the Late Jurassic to Early Cretaceous, accompanied by large-scale mineralization. Sr–Nd–Hf isotopic evidence of these granitic rocks suggested they were likely originated from a mixed source composed of lower crust and newly underplated basaltic crust. Assimilation-fractional crystallization (AFC) or crustal contamination possibly occurred in the magma evolution, and a much more addition of juvenile component to the source of the Early Cretaceous granitoids than that of Late Jurassic. The closure of Mongol-Okhotsk ocean and the break-off of the Mongol-Okhotsk oceanic slab at depth in the Jurassic triggered extensive magmatism and related mineralization in this region. The Jurassic intrusive activities was affected by both the subduction of the Palaeo-Pacific plate and the closure of Mongol-Okhotsk ocean. Less influence of the Mongol-Okhotsk tectonic regime on the Early Cretaceous magmatism, whereas, in contrast the Palaeo-Pacific tectonic regime possibly continued into the Cenozoic.</p